3 Search Results for "Zhang, Yingqian"

Document
DOI: 10.4230/OASIcs.Commit2Data.5
Real-Time Data-Driven Maintenance Logistics: A Public-Private Collaboration

Authors: Willem van Jaarsveld, Alp Akçay, Laurens Bliek, Paulo da Costa, Mathijs de Weerdt, Rik Eshuis, Stella Kapodistria, Uzay Kaymak, Verus Pronk, Geert-Jan van Houtum, Peter Verleijsdonk, Sicco Verwer, Simon Voorberg, and Yingqian Zhang

Published in: OASIcs, Volume 124, Commit2Data (2024)

Abstract
The project "Real-time data-driven maintenance logistics" was initiated with the purpose of bringing innovations in data-driven decision making to maintenance logistics, by bringing problem owners in the form of three innovative companies together with researchers at two leading knowledge institutions. This paper reviews innovations in three related areas: How the innovations were inspired by practice, how they materialized, and how the results impact practice.
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Willem van Jaarsveld, Alp Akçay, Laurens Bliek, Paulo da Costa, Mathijs de Weerdt, Rik Eshuis, Stella Kapodistria, Uzay Kaymak, Verus Pronk, Geert-Jan van Houtum, Peter Verleijsdonk, Sicco Verwer, Simon Voorberg, and Yingqian Zhang. Real-Time Data-Driven Maintenance Logistics: A Public-Private Collaboration. In Commit2Data. Open Access Series in Informatics (OASIcs), Volume 124, pp. 5:1-5:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{vanjaarsveld_et_al:OASIcs.Commit2Data.5,
  author =	{van Jaarsveld, Willem and Ak\c{c}ay, Alp and Bliek, Laurens and da Costa, Paulo and de Weerdt, Mathijs and Eshuis, Rik and Kapodistria, Stella and Kaymak, Uzay and Pronk, Verus and van Houtum, Geert-Jan and Verleijsdonk, Peter and Verwer, Sicco and Voorberg, Simon and Zhang, Yingqian},
  title =	{{Real-Time Data-Driven Maintenance Logistics: A Public-Private Collaboration}},
  booktitle =	{Commit2Data},
  pages =	{5:1--5:13},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-351-5},
  ISSN =	{2190-6807},
  year =	{2024},
  volume =	{124},
  editor =	{Haverkort, Boudewijn R. and de Jongste, Aldert and van Kuilenburg, Pieter and Vromans, Ruben D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Commit2Data.5},
  URN =		{urn:nbn:de:0030-drops-213626},
  doi =		{10.4230/OASIcs.Commit2Data.5},
  annote =	{Keywords: Data, Maintenance, Logistics, Optimization, Research, Project}
}
Document
Vision
DOI: 10.4230/TGDK.1.1.9
Trust, Accountability, and Autonomy in Knowledge Graph-Based AI for Self-Determination

Authors: Luis-Daniel Ibáñez, John Domingue, Sabrina Kirrane, Oshani Seneviratne, Aisling Third, and Maria-Esther Vidal

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
Knowledge Graphs (KGs) have emerged as fundamental platforms for powering intelligent decision-making and a wide range of Artificial Intelligence (AI) services across major corporations such as Google, Walmart, and AirBnb. KGs complement Machine Learning (ML) algorithms by providing data context and semantics, thereby enabling further inference and question-answering capabilities. The integration of KGs with neuronal learning (e.g., Large Language Models (LLMs)) is currently a topic of active research, commonly named neuro-symbolic AI. Despite the numerous benefits that can be accomplished with KG-based AI, its growing ubiquity within online services may result in the loss of self-determination for citizens as a fundamental societal issue. The more we rely on these technologies, which are often centralised, the less citizens will be able to determine their own destinies. To counter this threat, AI regulation, such as the European Union (EU) AI Act, is being proposed in certain regions. The regulation sets what technologists need to do, leading to questions concerning How the output of AI systems can be trusted? What is needed to ensure that the data fuelling and the inner workings of these artefacts are transparent? How can AI be made accountable for its decision-making? This paper conceptualises the foundational topics and research pillars to support KG-based AI for self-determination. Drawing upon this conceptual framework, challenges and opportunities for citizen self-determination are illustrated and analysed in a real-world scenario. As a result, we propose a research agenda aimed at accomplishing the recommended objectives.
Cite as

Luis-Daniel Ibáñez, John Domingue, Sabrina Kirrane, Oshani Seneviratne, Aisling Third, and Maria-Esther Vidal. Trust, Accountability, and Autonomy in Knowledge Graph-Based AI for Self-Determination. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 9:1-9:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{ibanez_et_al:TGDK.1.1.9,
  author =	{Ib\'{a}\~{n}ez, Luis-Daniel and Domingue, John and Kirrane, Sabrina and Seneviratne, Oshani and Third, Aisling and Vidal, Maria-Esther},
  title =	{{Trust, Accountability, and Autonomy in Knowledge Graph-Based AI for Self-Determination}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{9:1--9:32},
  ISSN =	{2942-7517},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.9},
  URN =		{urn:nbn:de:0030-drops-194839},
  doi =		{10.4230/TGDK.1.1.9},
  annote =	{Keywords: Trust, Accountability, Autonomy, AI, Knowledge Graphs}
}
Document
DOI: 10.4230/DagSemProc.08461.4
Creating incentives to prevent execution failures: an extension of VCG mechanism

Authors: Yingqian Zhang and Mathijs de Weerdt

Published in: Dagstuhl Seminar Proceedings, Volume 8461, Planning in Multiagent Systems (2009)

Abstract
When information or control in a multiagent planning system is private to the agents, they may misreport this information or refuse to execute an agreed outcome, in order to change the resulting end state of such a system to their benefit. In some domains this may result in an execution failure. We show that in such settings VCG mechanisms lose truthfulness, and that the utility of truthful agents can become negative when using VCG payments (i.e., VCG is not strongly individually rational). To deal with this problem, we introduce an extended payment structure which takes into account the actual execution of the promised outcome. We show that this extended mechanism can guarantee a nonnegative utility and is (i) incentive compatible in a Nash equilibrium, and (ii) incentive compatible in dominant strategies if and only if all agents can be verified during execution.
Cite as

Yingqian Zhang and Mathijs de Weerdt. Creating incentives to prevent execution failures: an extension of VCG mechanism. In Planning in Multiagent Systems. Dagstuhl Seminar Proceedings, Volume 8461, pp. 1-18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{zhang_et_al:DagSemProc.08461.4,
  author =	{Zhang, Yingqian and de Weerdt, Mathijs},
  title =	{{Creating incentives to prevent execution failures: an extension of VCG mechanism}},
  booktitle =	{Planning in Multiagent Systems},
  pages =	{1--18},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{8461},
  editor =	{J\"{u}rgen Dix and Edmund H. Durfee and Cees Witteveen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08461.4},
  URN =		{urn:nbn:de:0030-drops-18705},
  doi =		{10.4230/DagSemProc.08461.4},
  annote =	{Keywords: Mechanism design, multiagent planning}
}
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